[R] scatter3d() model.summary coefficients?

[angela baldo]

Hello All,

I am a R newbie and am probably misinterpreting something really
obvious...

In the Rcmdr package there is a scatter3d() function that can fit a
curve and also provide coefficients for the model.  If I'm understanding
this right, I think it's calling the lower level stats package function
lm(), which is the part that actually does the curve fitting.

Anyway, what has me perplexed is that the model summary from scatter3d()
has different coefficients than the one generated by lm().  However, the
actual surface plotted by scatter3d() looks like the function generated
by lm().

In the scatter3d() docs I didn't see anything about transforming the
coefficients or changing them somehow - perhaps I have not been looking
in the right place?

I'm using a Linux box: 2.6.17-1.2187_FC5smp, R version 2.3.1, Rcmdr
version 1.2-0, in case that helps.

Thanks very much for any enlightenment!

anja


Here's an example of the output on the same data by both functions.  If
anyone wants the dataset, let me know:

> scatter3d(samples$x1, samples$y, samples$x2, fit="linear",
residuals=TRUE, bg="white", axis.scales=TRUE, grid=TRUE,
ellipsoid=FALSE, xlab="x1", ylab="y", zlab="x2", model.summary=TRUE)
$linear

Call:
lm(formula = y ~ x + z)

Residuals:
      Min        1Q    Median        3Q       Max 
-0.096984 -0.022303  0.004758  0.029354  0.091188 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept)  0.708945   0.007005  101.20   <2e-16 ***
x            0.278540   0.011262   24.73   <2e-16 ***
z           -0.688175   0.011605  -59.30   <2e-16 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

Residual standard error: 0.03936 on 105 degrees of freedom
Multiple R-Squared: 0.972,      Adjusted R-squared: 0.9715 
F-statistic:  1822 on 2 and 105 DF,  p-value: < 2.2e-16 

> summary(lm(formula=samples$y~samples$x1+samples$x2))

Call:
lm(formula = samples$y ~ samples$x1 + samples$x2)

Residuals:
    Min      1Q  Median      3Q     Max 
-7865.0 -1808.6   385.8  2380.5  7394.9 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept) 92204.502   1323.217   69.68   <2e-16 ***
samples$x1    225.882      9.133   24.73   <2e-16 ***
samples$x2   -558.076      9.411  -59.30   <2e-16 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

Residual standard error: 3192 on 105 degrees of freedom
Multiple R-Squared: 0.972,      Adjusted R-squared: 0.9715 
F-statistic:  1822 on 2 and 105 DF,  p-value: < 2.2e-16